Diego Caballero

Protein design: Past, present, and future

Building on the pioneering work of Ho and DeGrado (J Am Chem Soc 1987, 109, 6751–6758) in the late 1980s, protein design approaches have revealed many fundamental features of protein structure and stability. We are now in the era that the early work presaged – the design of new proteins with practical applications and uses. Here we briefly survey some past milestones in protein design, in addition to highlighting recent progress and future aspirations.

New Insights into the Interdependence between Amino Acid Stereochemistry and Protein Structure

To successfully design new proteins and understand the effects of mutations in natural proteins, we must understand the geometric and physicochemical principles underlying protein structure. The side chains of amino acids in peptides and proteins adopt specific dihedral angle combinations; however, we still do not have a fundamental quantitative understanding of why some side-chain dihedral angle combinations are highly populated and others are not. Here we employ a hard-sphere plus stereochemical constraint model of dipeptide mimetics to enumerate the side-chain dihedral angles of leucine (Leu) and isoleucine (Ile), and identify those conformations that are sterically allowed versus those that are not as a function of the backbone dihedral angles ϕ and ψ. We compare our results with the observed distributions of side-chain dihedral angles in proteins of known structure. With the hard-sphere plus stereochemical constraint model, we obtain agreement between the model predictions and the observed side-chain dihedral angle distributions for Leu and Ile. These results quantify the extent to which local, geometrical constraints determine protein side-chain conformations.

Intrinsic α-helical and β-sheet conformational preferences: A computational case study of alanine

A fundamental question in protein science is what is the intrinsic propensity for an amino acid to be in an α‐helix, β‐sheet, or other backbone dihedral angle ( ϕ ‐ψ) conformation. This question has been hotly debated for many years because including all protein crystal structures from the protein database, increases the probabilities for α‐helical structures, while experiments on small peptides observe that β‐sheet‐like conformations predominate. We perform molecular dynamics (MD) simulations of a hard‐sphere model for Ala dipeptide mimetics that includes steric interactions between nonbonded atoms and bond length and angle constraints with the goal of evaluating the role of steric interactions in determining protein backbone conformational preferences. We find four key results. For the hard‐sphere MD simulations, we show that (1) β‐sheet structures are roughly three and half times more probable than α‐helical structures, (2) transitions between α‐helix and β‐sheet structures only occur when the backbone bond angle τ (NCαC) is greater than 110°, and (3) the probability distribution of τ for Ala conformations in the “bridge” region of ϕ ‐ψ space is shifted to larger angles compared to other regions. In contrast, (4) the distributions obtained from Amber and CHARMM MD simulations in the bridge regions are broader and have increased τ compared to those for hard sphere simulations and from high‐resolution protein crystal structures. Our results emphasize the importance of hard‐sphere interactions and local stereochemical constraints that yield strong correlations between ϕ ‐ψ conformations and τ.

Steric interactions determine side-chain conformations in protein cores.

We investigate the role of steric interactions in defining side-chain conformations in protein cores. Previously, we explored the strengths and limitations of hard-sphere dipeptide models in defining sterically allowed side-chain conformations and recapitulating key features of the side-chain dihedral angle distributions observed in high-resolution protein structures. Here, we show that modeling residues in the context of a particular protein environment, with both intra- and inter-residue steric interactions, is sufficient to specify which of the allowed side-chain conformations is adopted. This model predicts 97% of the side-chain conformations of Leu, Ile, Val, Phe, Tyr, Trp and Thr core residues to within 20°. Although the hard-sphere dipeptide model predicts the observed side-chain dihedral angle distributions for both Thr and Ser, the model including the protein environment predicts side-chain conformations to within 20° for only 60% of core Ser residues. Thus, this approach can identify the amino acids for which hard-sphere interactions alone are sufficient and those for which additional interactions are necessary to accurately predict side-chain conformations in protein cores. We also show that our approach can predict alternate side-chain conformations of core residues, which are supported by the observed electron density.

Equilibrium transitions between side chain conformations in leucine and isoleucine

Despite recent improvements in computational methods for protein design, we still lack a quantitative, predictive understanding of the intrinsic probabilities for amino acids to adopt particular side‐chain conformations. Surprisingly, this question has remained unsettled for many years, in part because of inconsistent results from different experimental approaches. To explicitly determine the relative populations of different side‐chain dihedral angles, we performed all‐atom hard‐sphere Langevin Dynamics simulations of leucine (Leu) and isoleucine (Ile) dipeptide mimetics with stereo‐chemical constraints and repulsive‐only steric interactions between non‐bonded atoms. We determine the relative populations of the different χ1 and χ2 dihedral angle combinations as a function of the backbone dihedral angles ϕ and ψ. We also propose, and test, a mechanism for inter‐conversion between the different side‐chain conformations. Specifically, we discover that some of the transitions between side‐chain dihedral angle combinations are very frequent, whereas others are orders of magnitude less frequent, because they require rare coordinated motions to avoid steric clashes. For example, to transition between different values of χ2, the Leu side‐chain bond angles κ1 and κ2 must increase, whereas to transition in χ1, the Ile bond angles λ1 and λ2 must increase. These results emphasize the importance of computational approaches in stimulating further experimental studies of the conformations of side‐chains in proteins. Moreover, our studies emphasize the power of simple steric models to inform our understanding of protein structure, dynamics, and design. Proteins 2015; 83:1488–1499.

Intrinsic α-helical and β-sheet conformational preferences: A computational case study of alanine: Intrinsic α-Helical and β-Sheet Conformational Preferences

A fundamental question in protein science is what is the intrinsic propensity for an amino acid to be in an α‐helix, β‐sheet, or other backbone dihedral angle ( ϕ ‐ψ) conformation. This question has been hotly debated for many years because including all protein crystal structures from the protein database, increases the probabilities for α‐helical structures, while experiments on small peptides observe that β‐sheet‐like conformations predominate. We perform molecular dynamics (MD) simulations of a hard‐sphere model for Ala dipeptide mimetics that includes steric interactions between nonbonded atoms and bond length and angle constraints with the goal of evaluating the role of steric interactions in determining protein backbone conformational preferences. We find four key results. For the hard‐sphere MD simulations, we show that (1) β‐sheet structures are roughly three and half times more probable than α‐helical structures, (2) transitions between α‐helix and β‐sheet structures only occur when the backbone bond angle τ (NCαC) is greater than 110°, and (3) the probability distribution of τ for Ala conformations in the “bridge” region of ϕ ‐ψ space is shifted to larger angles compared to other regions. In contrast, (4) the distributions obtained from Amber and CHARMM MD simulations in the bridge regions are broader and have increased τ compared to those for hard sphere simulations and from high‐resolution protein crystal structures. Our results emphasize the importance of hard‐sphere interactions and local stereochemical constraints that yield strong correlations between ϕ ‐ψ conformations and τ.

Intrinsic alpha-helical and beta-sheet preferences: A computational case study of Alanine

A fundamental question in protein science is what is the intrinsic propensity for an amino acid to be in an α‐helix, β‐sheet, or other backbone dihedral angle ( ϕ ‐ψ) conformation. This question has been hotly debated for many years because including all protein crystal structures from the protein database, increases the probabilities for α‐helical structures, while experiments on small peptides observe that β‐sheet‐like conformations predominate. We perform molecular dynamics (MD) simulations of a hard‐sphere model for Ala dipeptide mimetics that includes steric interactions between nonbonded atoms and bond length and angle constraints with the goal of evaluating the role of steric interactions in determining protein backbone conformational preferences. We find four key results. For the hard‐sphere MD simulations, we show that (1) β‐sheet structures are roughly three and half times more probable than α‐helical structures, (2) transitions between α‐helix and β‐sheet structures only occur when the backbone bond angle τ (NCαC) is greater than 110°, and (3) the probability distribution of τ for Ala conformations in the “bridge” region of ϕ ‐ψ space is shifted to larger angles compared to other regions. In contrast, (4) the distributions obtained from Amber and CHARMM MD simulations in the bridge regions are broader and have increased τ compared to those for hard sphere simulations and from high‐resolution protein crystal structures. Our results emphasize the importance of hard‐sphere interactions and local stereochemical constraints that yield strong correlations between ϕ ‐ψ conformations and τ.